日內回轉策略：做T策略

擇時交易：

 if date[-8:-3] != '14:55':if macd > 0 and macd_pre < 0:# 根據MACD>0則開倉,小于0則平倉if avaliable > df.iloc[-1, 0] * ContextInfo.Lots * 100:order_shares(ContextInfo.get_universe()[0], ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,ContextInfo.accountID)flage = Truesingleemited = TrueContextInfo.MarketPosition[ContextInfo.get_universe()[0]] += ContextInfo.Lotsprint (ContextInfo.get_universe()[0], 'open position at market price', ContextInfo.Lots, '股')elif macd < 0 and macd_pre > 0 and holding[ContextInfo.get_universe()[0]] >= ContextInfo.Lots:order_shares(ContextInfo.get_universe()[0], -ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,ContextInfo.accountID)flage = Falsesingleemited = Trueprint(ContextInfo.get_universe()[0], 'close position at market price', ContextInfo.Lots, '股')ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] -= ContextInfo.Lots# 臨近收盤時若倉位數不等于昨倉則回轉所有倉位

策略代碼全部：
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# coding:gbk
'''
回測模型示例（非實盤交易策略）本策略首先買入當前股票10000股
隨后根據60s的數據來計算MACD(12,26,9)線,并在MACD>0，MACD_pre<0的時候買入100股,MACD<0,MACD_pre>0的時候賣出100股
但每日操作的股票數不超過原有倉位,并于收盤前把倉位調整至開盤前的倉位
本策略需在個股分鐘線下運行
'''
import numpy as np
import pandas as pd
import talibdef init(ContextInfo):MarketPosition = {}ContextInfo.MarketPosition = MarketPosition  # 初始化持倉ContextInfo.set_universe([ContextInfo.stockcode + '.' + ContextInfo.market])ContextInfo.first = 0ContextInfo.Lots = 100  # 設定交易手數ContextInfo.day = [0, 0]ContextInfo.ending = 0ContextInfo.total = 10000ContextInfo.accountID = 'testS'def handlebar(ContextInfo):d = ContextInfo.barposif d < 35:returnstartdate = timetag_to_datetime(ContextInfo.get_bar_timetag(d - 35), '%Y%m%d%H%M%S')enddate = timetag_to_datetime(ContextInfo.get_bar_timetag(d), '%Y%m%d%H%M%S')##print startdate,enddatedate = timetag_to_datetime(ContextInfo.get_bar_timetag(d), '%Y-%m-%d %H:%M:%S')print('日期', date)flage = Falsesingleemited = Falsedf = ContextInfo.get_market_data(['close'], stock_code=ContextInfo.get_universe(), start_time=startdate,end_time=enddate, period=ContextInfo.period)# print dfif df.empty:return# print dfif ContextInfo.first == 0:order_shares(ContextInfo.get_universe()[0], ContextInfo.total, 'fix', df.iloc[-1, 0], ContextInfo,ContextInfo.accountID)flage = Truesingleemited = TrueContextInfo.first = 1ContextInfo.day[-1] = date[8:10]ContextInfo.turnaround = [0, 0]ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.totalreturnContextInfo.day[0] = date# 14:55:00之后不再交易if int(date[-8:-6] + date[-5:-3]) > 1455:returnavaliable = get_avaliable(ContextInfo.accountID, 'STOCK')holding = get_holdings(ContextInfo.accountID, 'STOCK')if ContextInfo.get_universe()[0] not in list(holding.keys()):holding[ContextInfo.get_universe()[0]] = 0# 計算MACD線if ContextInfo.total >= 0:recent_date = np.array(df.iloc[-35:, 0])macd = talib.MACD(recent_date)[0][-1]macd_pre = talib.MACD(recent_date)[0][-2]# 根據MACD>0則開倉,小于0則平倉if date[-8:-3] != '14:55':if macd > 0 and macd_pre < 0:# 根據MACD>0則開倉,小于0則平倉if avaliable > df.iloc[-1, 0] * ContextInfo.Lots * 100:order_shares(ContextInfo.get_universe()[0], ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,ContextInfo.accountID)flage = Truesingleemited = TrueContextInfo.MarketPosition[ContextInfo.get_universe()[0]] += ContextInfo.Lotsprint (ContextInfo.get_universe()[0], 'open position at market price', ContextInfo.Lots, '股')elif macd < 0 and macd_pre > 0 and holding[ContextInfo.get_universe()[0]] >= ContextInfo.Lots:order_shares(ContextInfo.get_universe()[0], -ContextInfo.Lots, 'fix', df.iloc[-1, 0], ContextInfo,ContextInfo.accountID)flage = Falsesingleemited = Trueprint(ContextInfo.get_universe()[0], 'close position at market price', ContextInfo.Lots, '股')ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] -= ContextInfo.Lots# 臨近收盤時若倉位數不等于昨倉則回轉所有倉位else:if ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] > ContextInfo.total:order_shares(ContextInfo.get_universe()[0],-(ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] - ContextInfo.total), 'fix',df.iloc[-1, 0], ContextInfo, ContextInfo.accountID)flage = Falsesingleemited = True# print ContextInfo.get_universe()[0], '回轉操作市價單平多倉', ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] - ContextInfo.total, '股'ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.totalif ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] < ContextInfo.total:order_shares(ContextInfo.get_universe()[0],(ContextInfo.total - ContextInfo.MarketPosition[ContextInfo.get_universe()[0]]), 'fix',df.iloc[-1, 0], ContextInfo, ContextInfo.accountID)flage = Truesingleemited = True# print ContextInfo.get_universe()[0], '回轉操作市價單開多倉', ContextInfo.total - ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] , '股'ContextInfo.MarketPosition[ContextInfo.get_universe()[0]] = ContextInfo.total# 更新過去的日期數據'''ContextInfo.day[-1] = ContextInfo.day[0]if singleemited:if flage:ContextInfo.paint('do_buy',1,-1,0,"yellow",'noaxis')ContextInfo.paint('do_sell',0,-1,0,"red",'noaxis')else:ContextInfo.paint('do_buy',0,-1,0,"yellow",'noaxis')ContextInfo.paint('do_sell',1,-1,0,"red",'noaxis')'''# ContextInfo.paint('holding',ContextInfo.MarketPosition[ContextInfo.get_universe()[0]],-1,0)def get_avaliable(accountid, datatype):result = 0resultlist = get_trade_detail_data(accountid, datatype, "ACCOUNT")for obj in resultlist:result = obj.m_dAvailablereturn resultdef get_holdings(accountid, datatype):holdinglist = {}resultlist = get_trade_detail_data(accountid, datatype, "POSITION")for obj in resultlist:holdinglist[obj.m_strInstrumentID + "." + obj.m_strExchangeID] = obj.m_nCanUseVolumereturn holdinglist